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Record W2750584020 · doi:10.12927/hcpol.2017.25194

Marijuana Use and Perceptions of Risk and Harm: A Survey among Canadians in 2016

2017· article· en· W2750584020 on OpenAlex
Eldon Spackman, Rebecca Haines‐Saah, Vishva M. Danthurebandara, Laura E. Dowsett, Tom Noseworthy, Fiona Clement

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueHealthcare policy · 2017
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLegalizationHarmCannabisRisk perceptionPerceptionEnvironmental healthPublic healthPsychologyMedicinePsychiatrySocial psychologyNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe marijuana use by Canadians and their perceptions of risk and harm. DESIGN: A cross-sectional, structured, online and telephone survey. PARTICIPANTS: A nationally representative sample of Canadians. METHODS: This survey used random probability sampling and targeted respondents based on age, sex, region and their expected response rate. RESULTS: Of the 20% of respondents reporting marijuana use in the past 12 months, they were more likely to be younger and male. The most common form of use was smoking, 79%. When asked about harmfulness, 42% and 41% responded that they considered marijuana more harmful than helpful to mental health and to physical health, respectively. When asked about driving under the influence, 71% responded that it was the same as alcohol. CONCLUSION: This research is important for health providers and policy makers seeking to maximize public health through clinical and legislative reform of non-medical use of marijuana.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.389
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it